The increasing use of wireless communication systems for voice-only communications, interactive Internet data, and multi-media applications, as well as higher data rate transmission requirements have consumed much of the available wireless spectrum. Recently, opportunistic usage of Licensed frequency bands have been utilized as a solution to spectral crowding problem by using cognitive radio (CR) systems (J. Mitola and G. Q. Maguire Jr., “Cognitive radio: making software radios snore personal,” IEEE Personal Communications, vol. 6, no.4, pp. 13-18, August 1999; T. Weiss and F. K. Jondral, “Spectrum pooling: an innovative strategy for the enhancement of spectrum efficiency,” IEEE Commun. Mag., vol. 42, no. 3, pp. 8-14. March 2004). Cognitive radio system are known in the art, and can be described as software defined radio with a “cognitive engine”, wherein the cognitive engine monitors the performance of the radio, by receiving signals from the antennas to determine the RF environment, channel conditions, link performance, etc., and configures the radio settings to comply with user requirements, operational limitations and possibly regulatory constraints. In response to the performance of the radio, and possibly user input, the cognitive engine configures the radio to adjust one or more factors including, waveform, protocol, operating frequency, etc., of the radio signal to meet a desired qualify of service.
A key point for the success of CRs is the ability to shape its signal spectrum as to achieve minimum interference to licensed users (LUs) operating in the used band. However, to achieve this objective, the system physical layer (PHY) needs to be highly flexible and adaptable. Future technologies will face spectral crowding, and coexistence of wireless devices will be a major problem. Considering the limited bandwidth availability, accommodating the demand for higher capacity and data rates is a challenging task, requiring innovative technologies that can offer new ways of exploiting the available radio spectrum, such as cognitive radio. (Mitola, J. and J. Maguire, G. Q., “Cognitive radio: making software radios more personal,” IEEE Personal Commun. Mag., vol. 6, no. 4, pp. 13-18, August 1999).
Multi-carrier techniques, specifically orthogonal frequency division multiplexing (OFDM), are commonly used in modern wireless communications systems and have the potential of fulfilling the requirements of CR. By dividing the spectrum into subbands that are modulated with orthogonal subcarriers, OFDM spectrum can be shaped with more ease compared to other signaling techniques. OFDM utilizes sinc-type pulses to represent symbols transmitted over subcarrier signals, resulting in large sidelobes. These sidelobes may interfere with the signal transmissions of neighboring legacy systems, causing adjacent channel interference (ACI) between the transmissions.
Disabling a set of OFDM subcarriers to create a spectrum null may not be sufficient to avoid interference to LU. Sidelobe suppression is a relatively new field, with only a few sidelobe suppression techniques available. These techniques transmit large volumes of information to the receiver to attain interference suppression. Techniques include guard bands on both sides of used OFDM spectrum coupled with windowing of the time-domain symbols (T. Weiss, J. Hillenbrand, A. Krohn, and F. K. Jondral. “Mutual interference in OPDM-based spectrum pooling systems,” in Proc. IEEE Veh. Technol. Conf., vol. 4, May 2004, pp. 1873-1877), interference cancellation carriers (CCs) (H. Yamaguchi, “Active interference cancellation technique for MB-OFDM cognitive radio,” in Proc. IEEE European Microwave Conf., vol. 2, October 2004, pp. 1105-1108; S. Brandes, I. Cosovic, and M. Schnell, “Reduction of out-of-band radiation in OFDM systems by insertion of cancellation carriers,” IEEE Commun. Lett., vol. 10, no. 6, pp. 420-422, 2006), or subcarrier weighting (I. Cosovic; S. Brandes, and M. Schnell, “Subcarrier weighting: a method for sidelobe suppression in OFDM systems.” IEEE Commun. Lett., vol. 10, no. 6, pp. 444-446, June 2006). CC techniques can significantly suppress OFDM sidelobes, as seen in FIG. 1, but result in an increase in the system peak-to-average-power ratio (PAPR) and the performance is sensitive to the cyclic prefix (CP) size. CC forces the transmitter and/or receiver to undertake significant computational analysis, increase the system complexity and introduce long delays. Moreover, due to the higher power used for the CCs, using this technique affects the spectral flatness of the transmitted signal and can increase the inter-carrier interference (ICI) effect in case of a Doppler spread or a frequency offset error at the receiver. On the other hand, subcarrier weighting method causes an increase in the system bit error rate (BER) and the interference reduction is not as significant as it is with the CC method.
Accordingly, a method for reducing signal interference while maximizing receiver resources is needed in the art.